Canada faces a critical challenge in artificial intelligence governance due to regulatory fragmentation, which may hinder innovation and place small and medium enterprises at a disadvantage. A recent workshop emphasized the need for “AI interoperability” to align regulatory frameworks and support the growth of Canadian organizations in a complex global environment.
On January 1, 2026, the Texas Responsible AI Governance Act (TRAIGA) came into effect, shifting AI regulation focus to intentional harm rather than accidental bias. This law fosters innovation, protects constitutional rights, and limits government overreach.
The government has demanded that social media platform X take immediate action after its AI chatbot, Grok, was used to create sexualized images of women and children without their consent. Technology Secretary Liz Kendall emphasized the need to uphold the law and prevent the spread of degrading content.
Campaigners criticize the government for delaying legislation against creating non-consensual sexualized deepfakes, amid public backlash over Elon Musk’s AI Grok generating harmful images.
A new federal executive order seeks to halt state and local regulation of artificial intelligence, arguing that fragmented laws could undermine U.S. competitiveness. It establishes a framework for a uniform national AI policy and directs federal agencies to limit conflicting state laws.
New Texas AI legislation, the Texas Responsible Artificial Intelligence Governance Act (TRAIGA), will take effect on January 1, 2026, aiming to regulate AI systems to prevent issues like discrimination and illegal content. Chris Schwegmann discusses how AI can enhance legal practice efficiency while ensuring ethical deployment.
With over 70 countries drafting AI regulations, global organizations face a complex and varied compliance landscape. Effective AI risk management requires strategic mapping of regulatory footprints, understanding key jurisdictional differences, and treating AI governance as an adaptive, ongoing process.
The surge in non-human identities (NHIs) and AI adoption is challenging identity security efforts, with organizations managing significantly more machine than human identities. As companies consolidate platforms for better management, security teams must adapt to growing complexity and risks.
The global Model Validation Platform Market is projected to grow from USD 1.84 billion in 2025 to USD 6.50 billion by 2033. Growth is driven by AI adoption and regulatory compliance in sectors like banking, healthcare, and telecom, with automated validation technologies enabling greater transparency and risk mitigation.
As organizations adopt AI in third-party risk management (TPRM), many lack the structured foundations and data governance necessary for success. Achieving AI readiness requires a disciplined, modular approach that balances innovation with accountability to enhance oversight effectively.